My answer was only about some numbers in the human brain at different scale levels, without any direct link with the number of bits. The number of bits reflects the choice of the modeler. The idea is to keep the number of bits as low as possible to ease the computations but it is always a very simplified representation of the reality.
The link between bits & neurons is stated in BAMI:
The bits in an SDR correspond to neurons in the brain, a 1 being a relatively active neuron and a 0 being a relatively inactive neuron.
When Numenta people model one cortical layer, I think that their SDR has as many bits as the number of minicolumns. The bits in those SDR correspond to minicolums in the brain, a 1 being an active minicolumn (please correct me if necessary).
Thus, an SDR of 2000 bits would mean a model of a macrocolumn of 2000 minicolumns. This number is one order of magnitude greater than the figure I gave (1 macrocolumn ~ 100 minicolumns). I guess it is simply because the HTM model is performing well with this size, not because it corresponds to the number of minicolumns in a macrocolumn.
On a side note, the term “cortical column” can refer to “minicolumn” or “macrocolumn” depending on the context.